title: Using administrative data to identify naturally occurring networks of physicians.
abstract: BACKGROUND
  Physicians naturally form networks. Networks could form a rational basis for Accountable Care Organizations (ACOs) for defined populations of Medicare beneficiaries.
  
  
  OBJECTIVE
  To use methods from network science to identify naturally occurring networks of physicians that might be best suited to becoming ACOs.
  
  
  METHODS
  Using nationally representative claims data from the Medicare program for CY 2006 on 51 hospital referral regions (HRRs), we used a network science-based community-detection algorithm to identify groups of physicians likely to have preestablished relationships. After assigning patients to networks based upon visits with a primary care physician, we examined the proportion of care delivered within communities and compared our results with potential ACOs organized around single hospitals.
  
  
  RESULTS
  We studied 4,586,044 Medicare beneficiaries from 51 HRRs who were seen by 68,288 active physicians practicing in those HRRs. The median community-based network ACO had 150 physicians with 5928 ties, whereas the median hospital-based network ACO had 96 physicians with 3276 ties. Among patients assigned to networks via their primary care physicians, seventy-seven percent of physician visits occurred with physicians in the community-based networks as compared with 56% with physicians in the hospital-based networks; however, just 8% of specialist visits were to specialists within the hospital-based networks as compared with 60% of specialist visits within the community-based networks. Some markets seemed better suited to developing ACOs based on network communities than others.
  
  
  CONCLUSIONS
  We present a novel approach to identifying groups of physicians that might readily function as ACOs. Organic networks identified and defined in this natural and systematic manner already have physicians who exhibit close working relationships, and who, importantly, keep the vast majority of care within the networks.
authors.affiliation: Department of Health Care Policy, Harvard Medical School, Boston, MA 02115, USA. landon@hcp.med.harvard.edu
authors.forename: Bruce E
authors.initials: BE
authors.lastname: Landon
authors.forename: Jukka-Pekka
authors.initials: JP
authors.lastname: Onnela
authors.forename: Nancy L
authors.initials: NL
authors.lastname: Keating
authors.forename: Michael L
authors.initials: ML
authors.lastname: Barnett
authors.forename: Sudeshna
authors.initials: S
authors.lastname: Paul
authors.forename: Alistair J
authors.initials: AJ
authors.lastname: O'Malley
authors.forename: Thomas
authors.initials: T
authors.lastname: Keegan
authors.forename: Nicholas A
authors.initials: NA
authors.lastname: Christakis
mesh_terms: D060866:Accountable Care Organizations / Q000458:organization & administration*; D000465:Algorithms; D019058:Community Networks; D006801:Humans; D007345:Insurance Claim Review / Q000706:statistics & numerical data; D007400:Interprofessional Relations; D006278:Medicare / Q000706:statistics & numerical data; D010820:Physicians / Q000458:organization & administration*; D010818:Practice Patterns, Physicians'; D011320:Primary Health Care / Q000458:organization & administration*; D014481:United States